With that said, it wasn’t encouraged because of significant performance penalties. When I used MongoDB, it just announced the support for multi-document transactions. MongoDB lacked multi-document transactions.It was slow, clunky, and tended to crash. Using Robo 3T as the default database browser felt like being transported into the year 2000.Up to above 20 seconds on a database that was less than 2GB in size. Querry times for the same query with different parameters (“Steve” was OK, but “Garry” wasn’t) varied by a factor of 100.To give some examples of problems we had: I worked with MongoDB in the past (not my choice, it was already there), and that wasn’t a pleasant ride.Not bite me in the least expected moment.Will just work - the less my time it needs, the better.Have a reasonable learning curve - I want to concentrate on delivering value, not get stuck in the docs for the first week.Handle a versatile load - background calculations are very computation heavy.You can read about my context here, here and here where I try to calculate 17 billion similarities I need a document database for storing denormalized entries that will: No matter where You read/heard/saw a recommendation of a product, always consider the context of the problem and the recommended solution. Slapping on any piece of technology into a system is fundamentally a bad idea.Why slapping on MongoDB isn’t the right idea? Why is indexing vital in document databases?.How does it work from the client’s perspective?.What MongoDB limits in the free version?.What features RavenDB limits in the free version?.What is missing from the free version when compared to the paid one?.Why slapping on MongoDB isn’t the right idea?.Here is a table of content to give you an overview and make it easier to see the sections: Table of content: This article started as a way to structurize the comparison process but grew a bit more ( just like my previous comparison).
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